公开(公告)号：US20200176004A1

公开(公告)日：2020-06-04

申请号：US16206823

申请日：2018-11-30

Applicant: Google LLC

Inventor： Willem Bastiaan Kleijn ,  Jan K. Skoglund ,  Alejandro Luebs ,  Sze Chie Lim

IPC: G10L19/02 ,  G10L25/30

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coding speech using neural networks. One of the methods includes obtaining a bitstream of parametric coder parameters characterizing spoken speech; generating, from the parametric coder parameters, a conditioning sequence; generating a reconstruction of the spoken speech that includes a respective speech sample at each of a plurality of decoder time steps, comprising, at each decoder time step: processing a current reconstruction sequence using an auto-regressive generative neural network, wherein the auto-regressive generative neural network is configured to process the current reconstruction to compute a score distribution over possible speech sample values, and wherein the processing comprises conditioning the auto-regressive generative neural network on at least a portion of the conditioning sequence; and sampling a speech sample from the possible speech sample values.

公开(公告)号：US20230368804A1

公开(公告)日：2023-11-16

申请号：US18144413

申请日：2023-05-08

Applicant: Google LLC

Inventor： Willem Bastiaan Kleijn ,  Jan K. Skoglund ,  Alejandro Luebs ,  Sze Chie Lim

IPC: G10L19/02 ,  G10L25/30

CPC classification number: G10L19/0204 ,  G10L25/30

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coding speech using neural networks. One of the methods includes obtaining a bitstream of parametric coder parameters characterizing spoken speech; generating, from the parametric coder parameters, a conditioning sequence; generating a reconstruction of the spoken speech that includes a respective speech sample at each of a plurality of decoder time steps, comprising, at each decoder time step: processing a current reconstruction sequence using an auto-regressive generative neural network, wherein the auto-regressive generative neural network is configured to process the current reconstruction to compute a score distribution over possible speech sample values, and wherein the processing comprises conditioning the auto-regressive generative neural network on at least a portion of the conditioning sequence; and sampling a speech sample from the possible speech sample values.

公开(公告)号：US20210366495A1

公开(公告)日：2021-11-25

申请号：US17332898

申请日：2021-05-27

Applicant: Google LLC

Inventor： Willem Bastiaan Kleijn ,  Jan K. Skoglund ,  Alejandro Luebs ,  Sze Chie Lim

IPC: G10L19/02 ,  G10L25/30

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coding speech using neural networks. One of the methods includes obtaining a bitstream of parametric coder parameters characterizing spoken speech; generating, from the parametric coder parameters, a conditioning sequence; generating a reconstruction of the spoken speech that includes a respective speech sample at each of a plurality of decoder time steps, comprising, at each decoder time step: processing a current reconstruction sequence using an auto-regressive generative neural network, wherein the auto-regressive generative neural network is configured to process the current reconstruction to compute a score distribution over possible speech sample values, and wherein the processing comprises conditioning the auto-regressive generative neural network on at least a portion of the conditioning sequence; and sampling a speech sample from the possible speech sample values.

公开(公告)号：US12062380B2

公开(公告)日：2024-08-13

申请号：US18144413

申请日：2023-05-08

Applicant: Google LLC

Inventor： Willem Bastiaan Kleijn ,  Jan K. Skoglund ,  Alejandro Luebs ,  Sze Chie Lim

IPC: G10L19/02 ,  G10L25/30

CPC classification number: G10L19/0204 ,  G10L25/30

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coding speech using neural networks. One of the methods includes obtaining a bitstream of parametric coder parameters characterizing spoken speech; generating, from the parametric coder parameters, a conditioning sequence; generating a reconstruction of the spoken speech that includes a respective speech sample at each of a plurality of decoder time steps, comprising, at each decoder time step: processing a current reconstruction sequence using an auto-regressive generative neural network, wherein the auto-regressive generative neural network is configured to process the current reconstruction to compute a score distribution over possible speech sample values, and wherein the processing comprises conditioning the auto-regressive generative neural network on at least a portion of the conditioning sequence; and sampling a speech sample from the possible speech sample values.

公开(公告)号：US11676613B2

公开(公告)日：2023-06-13

申请号：US17332898

申请日：2021-05-27

Applicant: Google LLC

Inventor： Willem Bastiaan Kleijn ,  Jan K. Skoglund ,  Alejandro Luebs ,  Sze Chie Lim

IPC: G10L19/02 ,  G10L25/30

CPC classification number: G10L19/0204 ,  G10L25/30

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coding speech using neural networks. One of the methods includes obtaining a bitstream of parametric coder parameters characterizing spoken speech; generating, from the parametric coder parameters, a conditioning sequence; generating a reconstruction of the spoken speech that includes a respective speech sample at each of a plurality of decoder time steps, comprising, at each decoder time step: processing a current reconstruction sequence using an auto-regressive generative neural network, wherein the auto-regressive generative neural network is configured to process the current reconstruction to compute a score distribution over possible speech sample values, and wherein the processing comprises conditioning the auto-regressive generative neural network on at least a portion of the conditioning sequence; and sampling a speech sample from the possible speech sample values.

公开(公告)号：US11024321B2

公开(公告)日：2021-06-01

申请号：US16206823

申请日：2018-11-30

Applicant: Google LLC

Inventor： Willem Bastiaan Kleijn ,  Jan K. Skoglund ,  Alejandro Luebs ,  Sze Chie Lim

IPC: G10L19/02 ,  G10L25/30

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coding speech using neural networks. One of the methods includes obtaining a bitstream of parametric coder parameters characterizing spoken speech; generating, from the parametric coder parameters, a conditioning sequence; generating a reconstruction of the spoken speech that includes a respective speech sample at each of a plurality of decoder time steps, comprising, at each decoder time step: processing a current reconstruction sequence using an auto-regressive generative neural network, wherein the auto-regressive generative neural network is configured to process the current reconstruction to compute a score distribution over possible speech sample values, and wherein the processing comprises conditioning the auto-regressive generative neural network on at least a portion of the conditioning sequence; and sampling a speech sample from the possible speech sample values.